Abstract: We present a model of fire spread in Mediterranean and Middle-Eastern (MME) cities. The model accounts for the characteristic properties of MME cities: inflammable constructions and vegetation between constructions that becomes highly flammable during long and dry summers. We develop the model following the general rules proposed by Lee and Davidson in their empirically driven model of urban fire spread for the US city while establishing a new MME data generation algorithm for non-flammable constructions. The model is applied to a residential neighborhood in Haifa, Israel. Results demonstrate that unlike in the US, in MME cities interconstruction vegetation is the main mechanism of fire spread. Heterogeneity of the vegetation cover generates significant spatial variation of expected burnt area; in these circumstances, the model provides critical knowledge about the most vulnerable urban spots. Shaham, Yonatan and Benenson, Itzhak, “Modeling Urban Fires in Mediterranean and Middle-Eastern Cities”, Proceedings of the 2016 IEEE International Symposium on Technologies for Homeland Security, DOI: 10.1109/THS.2016.7568962 Link: http://ieeexplore.ieee.org/document/7568962/

1. Modeling Urban Fires in Mediterranean and Middle-
Eastern Cities
Yonatan Shaham
Porter School of Environmental Studies, Geosimulation
Lab, Department of Geography and Human Environment
Tel Aviv University
Tel Aviv, Israel
yjonas83@gmail.com
Itzhak Benenson
Geosimulation Lab, Department of Geography and Human
Environment
Tel Aviv University
Tel Aviv, Israel
bennya@post.tau.ac.il
Abstract—We present a model of fire spread in
Mediterranean and Middle-Eastern (MME) cities. The model
accounts for the characteristic properties of MME cities:
inflammable constructions and vegetation between constructions
that becomes highly flammable during long and dry summers.
We develop the model following the general rules proposed by
Lee and Davidson in their empirically driven model of urban fire
spread for the US city while establishing a new MME data
generation algorithm for non-flammable constructions. The
model is applied to a residential neighborhood in Haifa, Israel.
Results demonstrate that unlike in the US, in MME cities inter-
construction vegetation is the main mechanism of fire spread.
Heterogeneity of the vegetation cover generates significant spatial
variation of expected burnt area; in these circumstances, the
model provides critical knowledge about the most vulnerable
urban spots.
Keywords—fire modeling, inflammable wall, secondary
disasters, arid climate.
I. INTRODUCTION
Multiple fires in cities are frequent secondary-disasters,
following earthquakes, tsunamis, wars, industrial catastrophes,
and severe wild-land fires. Lack of firefighting forces in this
case may result in the widespread of the fire. In dry climate
zones, this is defined by easily igniting urban vegetation which
spreads fire to upper floors and to distant buildings.
Preparedness and response to multi-source fires demand
recognition of the critical urban areas, where the fire damage is
the highest, and which should be thus prioritized for fire
department suppression. This requires spatially explicit city-
scale model of fire spread in the city. Recent models of urban
fires have focused on the US and Japan cities and assumed that
the majority of constructions are flammable [1] [2] [3] [4]. To
model fire spread in Mediterranean and Middle-Eastern
(MME) cities, one should account for (1) non-flammability of
the majority of constructions and (2) for vegetation that fill
inter-building space, and is highly flammable during the long
summers that last up to 8 months. We propose to establish such
model modifying the rules proposed by Lee and Davidson
("L&D rules") in their empirically driven model of urban fire
in the US city [3]. In what follows we present the MME fire
model and apply it to the residential neighborhood in Haifa,
Israel.
II. MODIFICATION OF THE L&D RULES FOR THE MME
CITY
A. MME model structure
The L&D rules focus on the duration of three major
burning phases of compartment fires: fire growth, fully
developed fire, and fire decay. The duration of each phase is
estimated using empirical equations, which parameters are the
type and amount of fuel, the dimensions of the rooms’ 3D
envelope, and the size and form of the rooms' openings. When
the fire reaches the "fully developed" phase, it can spread to
other rooms and buildings in four ways: (1) burn through walls
and ceilings, (2) direct ignition by flame impingement through
doors and windows or burning vegetation, (3) heat radiation
from flames and gas, and (4) firebrands from burning roofs [3].
In MME cities, buildings' walls and ceilings are, usually,
nonflammable, but the inter-buildings vegetation is highly
flammable. Respectively, in the MME model: (1) fire cannot
spread through walls and ceilings, (2) vegetation can be ignited
by nearby constructions and ignite other constructions through
windows or firebrands, and (3) initial ignition may happen not
only in the room, but also in the vegetated space. The MME
model is developed as a GAMA [5] application and applied to
a residential neighborhood in central Haifa, Israel (Fig. 1).
Fig. 1. Study area in Haifa, Israel, where the MME fire spread model was
applied.

2. The case study area contains 86 buildings with a total of
2,960 rooms of 87,500m2
floor area. A GIS layer of
constructions’ footprints in Haifa was provided by the Survey
of Israel. Haifa Municipal Building File Archive was used to
retrieve constructions’ plans, including the internal partitioning
of buildings into rooms, position and size of windows and
doors, and flammability of roofs. Aerial photos were used to
identify and to classify vegetation. Following [3], indoor fuel
load was estimated to be 16 kg/m2
of wood equivalent fuel.
B. Comparison to experimental results
To validate the MME fire model at the level of single room
and single construction we exploited the Lennon and Moore's
(2003) series of fire experiments with nonflammable
constructions [6], which provided time-temperature curves for
10 experimental full-scale fires in a large room built from
concrete blocks for different configurations of openings and
fire loads. The experimental and model temperatures and
durations of the burning phases are presented in Table I.
TABLE I. COMPARING MODEL AND FIRE EXPERIMENTS RESULTS
Parameter
One opening Two openings
MME
model
Experiment
(STD)
MME
model
Experiment
(STD)
Time to fully developed
phase
12:17 13:20 (4:42) 13:07 7:30 (2:30)
Time to decay phase 32:45 33:20 (4:42) 35:00 26:15 (4:09)
Time to total burn 40:56 71:40 (6:14) 43:45 83:45 (8:11)
Average temperature during
fully developed fire (C)
1141 1322 (24.4) 1157 1343 (7.7)
As can be seen, in the case of one window, the fit between
the MME fire model output and the experiment is very good
for the two first parameters and worse for the third one.
However, fire spreads during the fully-developed phase only
and, thus, the difference in the total burning time does not
affect the modeled fire spread. Note that the simulated
temperature is about 0.85 of the temperature measured in
experiment. However the effect of this deviation in the city is
very limited as affecting fire spread by radiation only. This
phenomenon is hardly possible in the MME cities where the
gaps between constructions are large, 4-6 meters.
In the case of two windows, all fire phases in the model last
50-100% longer than in the experiment. However, in reality,
the fraction of rooms of this kind is low and most of them are
on buildings’ corners. To verify the consequences of this
discrepancy, in what follows we also used a “tuned” model in
which a two-window room burns 1.7 times faster than in the
original L&D rules. The results, given in Table II below,
indicate that the influence of two-window rooms is
insignificant in all investigated scenarios.
III. MME FIRE MODEL STUDY
Spatially explicit modeling of the fire spread demands
knowledge of the partitioning of construction floors into rooms
and the locations of windows and doors. Usually, these are not
available. To overcome the lack of data, Lee and Davidson [3]
proposed an algorithm to partition constructions’ footprints into
square rooms, and then connected adjacent rooms by doors
(“L&D algorithm” below). However, in MME cities,
apartments of the same floor exit to a corridor that is almost
empty of fuel (Fig. 2 left). In addition, the doors to the corridor
are usually made of metal with high degree of fire resistance.
Thus, fire spread between apartments of the same floor is very
unlikely and the partitioning algorithm should account for that.
To reflect these differences we implement a new "MME floor
partitioning” algorithm that, first, partitions the floor into
apartments of a typical size and second, partitions every
apartment into rooms of typical size connected by doors (Fig. 2
right).
Fig. 2. Left: Typical corridor in an MME building. Right: Algorithm of floor
partitioning into apartments and rooms.
To test the importance of adjusted floor partitioning, we
compared the model's outputs in four scenarios: (1) MME
model with real plans of the buildings' internal structure,
digitized from the municipal archive, (2) MME model with
MME algorithm of floor partitioning into apartments and
rooms, (3) MME model with L&D algorithm of floor
partitioning into rooms, and (4) the “tuned model” with real
plans of the buildings' internal structure which is used to study
the effect of model deviations from experimental results in the
case of rooms with two windows.
Fire dynamics in each scenario were first investigated for
the real Haifa buildings and vegetation patterns. Then, in order
to understand the role of vegetation, all scenarios were re-run
with all vegetation removed. In all scenarios, one room in the
study area was randomly selected and ignited. The simulation
was run at a time step of 30 seconds until either the fire
decayed without external intervention, or maximal simulation
time of 120 minutes was reached. In all scenarios, vegetation
burning speed was set to the lowest typical to the study area,
10m/hour. Wind speed was 5.2m/s from the north-west,
according to [7].
IV. RESULTS AND DISCUSSION
Model outputs are given on Table II. The real partition and
MME partitioning algorithm are very close, while the L&D
algorithm leads to an overshoot. The output of the “tuned
model” scenarios results does not differ from the outputs of
two first scenarios due to the low number of two-window
rooms in the buildings of the area. The presence of vegetation
increases fire spread significantly.
Fig. 3 presents distribution of the burnt area for the scenario
of real building plans. The variation of the burnt area size is

3. essential and is caused by variation in the distance between the
window and the nearest vegetation and the vegetation pattern
around the apartment (Fig. 4).
TABLE II. MEAN BURNT AREA AND BURNT AREA STANDARD ERROR (IN
M2
) OVER 450 REPETITIONS OF EACH SCENARIO
Vegetation
Real partition
of building into
apartments
MME
partition
algorithm
“Tuned model,”
real partition into
apartments
L&D
partition
algorithm
Removed 262 (17) 296 (13) 307 (18) 730 (33)
Regular 422 (24) 440 (26) 432 (24) 1068 (46)
Fig. 3. Distribution of burnt area size, scenario of real building plans and real
vegentation pattern
Fig. 4. The expected burnt area for an single ignition in the area’s building.
Development of burnt area in representive buildings (marked by circles) is
given in Fig. 5.
The temporal dynamics of the burnt area for three selected
buildings marked in Fig.3 are showed on Fig. 5. As can be
seen, the variation increases significantly with the mean. It is
also noticed that for the cases where fire spread is low, most of
the spread occurs during the first 30 minutes.
The model thus makes it possible to recognize urban
locations where the consequences of fire will be most
dangerous and to predict these consequences. In this way, we
provide the infrastructure for fire brigade decision-making.
Fig. 5 Dynamics of burnt area for the selected buildings (marked in Fig. 4),
mean and standard error for 50 runs.
V. FUTURE DEVELOPMENT
The MME model will be further investigated and then
applied to the case of multiple-ignitions in the Mediterranean
and Middle Eastern cities. We plan to study the effect of
simultanoues ignitions occuring in both constructions and
vegetation. Our ultimate goal is to identify the critical patterns
of ignitions that will lead to severe fire spreads and to propose
firefighting strategies for these circumstances.
ACKNOWLEDGMENT
We would like to thank Yulia Grinblat (Geosimulation Lab,
Department of Geography and Human Environment, Tel Aviv
University) and Marina Toger (ComplexCity research lab,
Faculty of Architecture and Town Planning, Technion) for
sharing high-resolution data on Haifa vegetation.
REFERENCES
[1] S. Li and R. A. Davidson, "Application of an Urban Fire Simulation
Model," Earthquake Spectra, vol. 29, no. 4, pp. 1369-1389, 2013.
[2] S. W. Lee, Modelling post-earthquake fire spread - PhD Dissertation,
Ithaca, NY: Cornell University, 2009.
[3] S. W. Lee and R. A. Davidson, "Physics-Based Simulation Model of
Post-Earthquake Fire Spread," Journal of Earthquake Engineering, pp.
670-687, 2010.
[4] K. Himoto and T. Tanaka, "Development and validation of a physics-
based urban fire spread model," Fire Safety Journal, no. 43, pp. 477-497,
2008.
[5] A. Grignard, P. Taillandier, B. Gaudou, D.-A. Vo, N.-Q. Huynh and A.
Drogoul, "GAMA 1.6: Advancing the Art of Complex Agent-Based
Modeling and Simulation," Lecture Notes in Computer Science, vol.
Vol. 8291 , pp. 117-131, 2013.
[6] T. Lennon and D. Moore, "The natural fire safety concept—full-scale
tests at Cardington," Fire Safety Journal, vol. 38, pp. 623-643, 2008.
[7] Israeli Meteorological Service, "Wind speed and azimuth records 2006-
2011, Haifa University Station," Israeli Meteorological Service, 2012.
1. Extreme
danger
2. Medium
danger
3. Minimal
danger